1. Field of the Invention
The invention relates to the field of medical imaging. More particularly, the present invention relates to bone scans, bone lesions, and bone disease assessment.
2. Discussion of the Related Art
Bone tumors may originate in bone or they may originate in other sites and spread (metastasize) to the skeleton. For example, secondary tumors in the bone frequently result from metastasized prostate cancer. Images from bone scans reveal lesions associated with primary bone or metastatic cancer and their interpretations are used extensively in the diagnosis and treatment of the disease.
A few computer-aided lesion detection systems have been reported for bone scans. These techniques have included semi-automated image segmentation programs that are frequently too time-consuming for use in a clinical setting such as those of Erdi et al. and Yin et al. The semi-automated approach described by Erdi et al. requires that the user insert a seed point in each metastatic region on the image, a process that is nontrivial, considering that patients with bone metastases often have multiple disease sites.1 1Erdi Y E, Humm J L, Imbriaco M, Yeung H, Larson S M, Quantitative bone metastases analysis based on image segmentation. J Nucl Med 1997; 38:1401-1406. See also Yin T K, Chiu N T, A computer-aided diagnosis for locating abnormalities in bone scintigraphy by a fuzzy system with a three-step minimization approach. IEEE Trans Med Imaging 2004; 23:639-654.
More recently, a fully automated method developed by Sadik et al. combines bone lesion detection by image segmentation with scan evaluation through an artificial neural network to classify patients by their probability of bone metastasis, resulting in a binary grading of scans as having probable “bone metastases” or probable “no bone metastases.”2 2See Sadik M, Jakobsson D, Olofsson F, Ohlsson M, Suurkula M, Edenbrandt L., A new computer-based decision-support system for the interpretation of bone scans. Nucl Med Commun 2006; 27:417-423.
Although this system showed a good correlation with physician-determined estimates of the probability of bone metastases, the system does not provide a quantitative metric for the comparison of consecutive scans nor a means of assessing treatment outcomes.
Importantly, none of the reported outcomes have been studied prospectively in relation to true measures of patient benefit such as reduction in skeletal-related events or prolongation of life, measures that form the basis for regulatory approvals.
Conversely, systems for image enhancement have been developed to normalize images from consecutive scans for ease of physician interpretation but have not attempted lesion identification.3 3Jeong C B, Kim K G, Kim T S, Kim S K, Comparison of image enhancement methods for the effective diagnosis in successive whole-body bone scans. J Digit Imaging 2011; 24:424-436.
Quantitative assessment by bone scintigraphy of metastatic bone disease burden in prostate cancer has been previously performed, including the development of metrics such as bone scan index (BSI) and percentage of the positive area on a bone scan (% PABS).4 4 Imbriaco M, Larson S M, Yeung H W, Mawlawi O R, Erdi Y, Venkatraman E S, et al., A new parameter for measuring metastatic bone involvement by prostate cancer: the Bone Scan Index. Clin Cancer Res 1998; 4: 1765-1772. See also Noguchi M, Kikuchi H, Ishibashi M, Noda S., Percentage of the positive area of bone metastasis is an independent predictor of disease death in advanced prostate cancer. Br J Cancer 2003; 88:195-201.
Both BSI and % PABS have undergone initial evaluation as prognostic factors for patients with prostate cancer, but the methods used to calculate these metrics have been time-consuming, requiring extensive manual annotation of bone scans. Evaluation of % PABS and BSI as feasible metrics for the assessment of treatment response is ongoing.5 5 Yahara J, Noguchi M, Noda S., Quantitative evaluation of bone metastases in patients with advanced prostate cancer during systemic treatment. BJU Int 2003; 92:379-384. See also Morris M J, Jia X, Larson S M, Kelly A, Mezheritzky I, Stephenson R D, et al., Post-treatment serial bone scan index (BSI) as an outcome measure predicting survival. Presented at: Genitourinary Cancers Symposium 2008;
While computer-aided detection (CAD) systems have been previously applied to bone scan analysis, they lack features in embodiments of the present invention. For example, such known systems have typically addressed lesion detection only on a single scan from a patient, without comparing successive scans.